DocumentCode :
67623
Title :
A Hyper-Heuristic Scheduling Algorithm for Cloud
Author :
Chun-Wei Tsai ; Wei-Cheng Huang ; Meng-Hsiu Chiang ; Ming-Chao Chiang ; Chu-Sing Yang
Author_Institution :
Dept. of Appl. Inf. & Multimedia, Chia Nan Univ. of Pharmacy & Sci., Tainan, Taiwan
Volume :
2
Issue :
2
fYear :
2014
fDate :
April-June 1 2014
Firstpage :
236
Lastpage :
250
Abstract :
Rule-based scheduling algorithms have been widely used on many cloud computing systems because they are simple and easy to implement. However, there is plenty of room to improve the performance of these algorithms, especially by using heuristic scheduling. As such, this paper presents a novel heuristic scheduling algorithm, called hyper-heuristic scheduling algorithm (HHSA), to find better scheduling solutions for cloud computing systems. The diversity detection and improvement detection operators are employed by the proposed algorithm to dynamically determine which low-level heuristic is to be used in finding better candidate solutions. To evaluate the performance of the proposed method, this study compares the proposed method with several state-of-the-art scheduling algorithms, by having all of them implemented on CloudSim (a simulator) and Hadoop (a real system). The results show that HHSA can significantly reduce the makespan of task scheduling compared with the other scheduling algorithms evaluated in this paper, on both CloudSim and Hadoop.
Keywords :
cloud computing; knowledge based systems; scheduling; CloudSim; HHSA; Hadoop; cloud computing systems; hyper-heuristic scheduling algorithm; rule-based scheduling algorithms; Cloud computing; Heuristic algorithms; Pricing; Scheduling algorithms; Time complexity; Cloud computing; and Hadoop; evolutionary algorithm; scheduling;
fLanguage :
English
Journal_Title :
Cloud Computing, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-7161
Type :
jour
DOI :
10.1109/TCC.2014.2315797
Filename :
6784130
Link To Document :
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